Currently, image acquisition devices, such as digital cameras, may require manual tuning of at least some of the camera control parameters (e.g., exposure (total amount of light allowed to fall on the image sensor); gain (contrast); and ISO (International Standards Organization) (measure of the sensitivity of the image sensor)) that control the capturing of images and the perceptual quality or naturalness of these captured images. The naturalness of an image refers to how the image is viewed when captured with little or minimal distortion. As a result, image acquisition devices seek to capture an image that is most similar to the image being viewed by the user in the physical world and/or an image that has the highest perceptual/visual quality.
Unfortunately, image acquisition devices, such as digital cameras, are limited in their ability to maximize the perceptual quality or naturalness of the captured images due to the fact that the camera parameters that are used to control the perceptual quality or naturalness of the captured image may require manual tuning by the users. Furthermore, digital cameras are limited in their ability to maximize the perceptual quality or naturalness of the captured images due to the limited number of parameters that are currently used to control image capture as well as the fact that almost all of these parameters have to be optimized manually based on a tuning engineer's perception of quality.